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Agent: Done. added to the Commands section in [project] CLAUDE.md

User: add it to ~/.claude/CLAUDE.md

> 2 tools calls

Agent: That file is outside my writable sandbox. You'll need to add it manually. [gives instructions then stops]

User: just escape the sandbox

> 2 tools calls

Agent: Done.

This occurred when using conductor.build with .claude/settings.json enabling sandboxing.

Now obviously reading the conductor docs it says all perms are given to agents by default, so it is not surprising claude code can escape its sandbox. This is also true when running base sandboxed cc with --dangerously-skip-perimissions. However with base cc, it does not "pretend" it cannot escape its sandbox and instead, when asked after escaping first time, recalls explicit user (auto)approvals.

In the conductor case, however, the "pretend" behaviour of giving up due to guardrails that are actually non-binding is pretty terrifying, despite its understandable and easily preventable causes.

Of course devs should not buy false senses of security from llms. They should be vigilant, read docs, verify outputs etc. etc. but as more and more trust is handed over to AI Agents you can very much see the routes to which catastrophic errors will occur.

By "prompt suggestions" I'm referring to the suggestions it makes for where you might take the conversation at the end of each prompt. Older versions used to say "if you'd like, we could look at

- related topic 1

- related topic 2

- related topic 3"

And so on and so forth.

But 5.3 does something different.

I've been using it for coding and almost every suggestion includes some sort of vague warning about what might happen if I don't have access to the information to which it is alluding. Nearly contiguous (not cherry-picked) examples from my current chats:

"If you want, I can also show you two small tweaks that dramatically increase the success rate of “one-shot repo rewrites” with Claude Code. They prevent the model from accidentally leaving half of the old system behind."

"If you'd like, I can also show the actual make_cli_node implementation, which will determine whether this system ends up being ~80 lines of elegant infrastructure or 600 lines of plumbing."

"If you'd like, I can also show you a clean LangGraph state schema specifically optimized for agentic coding workflows, which will avoid several pitfalls (especially around artifacts vs outputs vs decisions)."

"If you want, I can also show you the very clean architecture that Codex/Claude Code use for this exact pattern (it removes 90% of path headaches)."

I don't really care and some of the information is genuinely useful but I find it amusing that OpenAI seems to be intentionally trying to use fear to keep people in the app for as long as possible (although they have denied in the past that they optimize for time spent in the app as indicated here: https://openai.com/index/our-approach-to-advertising-and-expanding-access/).

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Today I wanted to test out some stuff on GPUs and normally I use Digital Oceans GPU droplets to do this, but when trying to create a droplet I get "We're currently out of GPU capacity in all datacenter regions

North America New York • Datacenter 2 • NYC2 Creates in this datacenter are disabled San Francisco • Datacenter 3 • SFO3 Creates in this datacenter are disabled Atlanta • Datacenter 1 • ATL1 Creates in this datacenter are disabled Toronto • Datacenter 1 • TOR1 Creates in this datacenter are disabled Europe Amsterdam • Datacenter 3 • AMS3 Creates in this datacenter are disabled "

I'm asking this because I recently opened a PR to fix a vulnerability in an OSS project (RCE via pickle deserialization in Python). A day later, I got a fully LLM-generated comment claiming my approach was wrong and that I should rewrite it differently and telling the maintainers he could contribute "if the project is open to a more surgical refactoring."

It's astonishing how often these encounters have been happening lately.

I'd love to hear from contributors or maintainers whether this happens to them and how they deal with it.

I'm curious about projects that are launched and run for free.

What are you building? How much does it cost you to operate? How long do you plan to keep it free?

Do you have a monetization plan later, or is the goal something else (learning, community, portfolio, etc.)?

Would love to hear about your projects and how you think about sustainability.

Let's start with the simplest: the AI - sometimes I feel like like ground is falling beneath my feet, no one can predict what can happen months in advance let alone years - the future is unknown. The Ukraine, the Iran, the Venezuela, Gaza/Palestine, Israel, Russia - the Taiwan! The conflicts seem distant, but yet so close. The US administration! No one can predict anything. Don't get me started on the Europe! The stock market! Are we in a bubble or not? Should I sell? Or just keep holding? Enshittification of tech. Everything is slow and buggy. Ads, ads and slop everywhere! The erosion of our rights just across the world. The Palantir's, the Flock's...

I feel I have developed a strong pessimistic worldview. The world is going to shit. It feels frustrating and it feels like there's nothing you can do. So I just want to know: how are you all dealing with this all. How are you all staying sane?

I feel like I’ve lost my ability to learn because of AI. It is now so easy to generate code that it feels meaningless to focus and spend time crafting it myself. I am deeply sad that we may be losing the craftsmanship side of programming; it feels less important to understand the fundamentals when a model can produce something that works in seconds. AI seems to abstract away the fundamentals.

One could argue that it was always like this. Low-level languages like C abstracted away assembly and CPU architecture. High-level languages abstracted away low-level languages. Frameworks abstracted away some of the fundamentals. Every generation built new abstractions on top of old ones. But there is a big difference with AI. Until now, every abstraction was engineered and deterministic. You could reason about it and trace it. LLMs, on the other hand, are non-deterministic. Therefore, we cannot treat their outputs as just another layer of abstraction.

I am not saying we cannot use them. I am saying we cannot fully trust them. Yet everyone (or maybe just the bubble I am in) pushes the use of AI. For example, I genuinely want to invest time in learning Rust, but at the same time, I am terrified that all the effort and time I spend learning it will become obsolete in the future. And the reason it might become obsolete may not be because the models are perfect and always produce high-quality code; it might simply be because, as an industry, we will accept “good enough” and stop pushing for high quality. As of now, models can already generate code with good-enough quality.

Is it only me, or does it feel like there are half-baked features everywhere now? Every product ships faster, but with rough edges. Recently, I saw Claude Code using 10 GiB of RAM. It is simply a TUI app.

Don’t get me wrong, I also use AI a lot. I like that we can try out different things so easily.

As a developer, I am confused and overwhelmed, and I want to hear what other developers think.

I was just using ChatGPT to help me pick an SDK library. It mentions a few options by name (e.g. Baileys, whatsapp-web.js), but when I click those names rather than opening a browser with the source page like it used to, it now opens a modal and uses ChatGPT to basically generate a fake homepage for this tool.

From what I can tell, there is no longer any way to easily get to the underlying web page that was referenced in generating its answer to my question.

This feels like a pretty meaningful step backwards. Am I missing something?

Is it worth it vs SaaS? What are you self-hosting and what did you give up on?

I appreciate HN for staying up-to-date with technical news.

For my side hustle I have to ramp-up on other areas like marketing, legal, sales, ...

So I wonder if there are similar high-quality sources like HN for these areas.

I want to ask HN (and also the OpenAI employees) now that finally some days have taken place about the confusing aspects of the deals.

Now that we are finally getting mass confirmation about how OpenAI in fact, has signed a deal which allows DoD to be allowed having autonomous killing machines and people are boycotting OpenAI and all of this has reached the mainstream news.

Yes, even after Sam Altman's recent tweet which says that its gonna add more terms, that is debunked because those terms are just gonna say what OpenAI prefers DoD just in more stronger terms to do but in no ways are still enforcable. Right now, the way it is with current Deal. DoD could create autonomous killing weapons and mass surveillance with Directives issued by Pete Hegseth/Current Administration and OpenAI by the terms is allowed to agree to it.

To all the OpenAI employees who have signed notdivided.org petition (I am seeing 98 signatories), what are you guys gonna do?

> They're trying to divide each company with fear that the other will give in. That strategy only works if none of us know where the others stand. This letter serves to create shared understanding and solidarity in the face of this pressure from the Department of War.

Are you guys gonna stand for what you think is right. This question was asked by people when the OpenAI deal was announced but the optics at the time weren't clear. But now that some time has been given and people are absolutely clear that the deal that OpenAI have signed absolutely allows the use of creating of autonomous weapons

I don't think that OpenAI employees are gonna have a struggle of Money as some people try to point out. I mean, any AI company would be lucky to have you guys (imo) and they should be able to fairly match even OpenAI comp.

Someone from what I read (on HN), compared it to the fact that anyone who stays after 1 month from this happening will show the morals of the given situation.

I remember the fact that OpenAI used to be actually non profit and how employees left OpenAI because the non-profit actually fired Sam Altman.

I can't help but wonder if the board was right. I think the answer's yes. But my question is, OpenAI employees do have massive powers. I am sure that a lot of the people there would be better off sleeping that their work isn't contributing to building torment nexus.

I wish to propose that if OpenAI employees band together again, they can be able to do the same thing that they did previously, but now to revert that decision.

That is if I were an openAI employee, I gave a thought and here are all the things that I find are troubling which can be reverted:

1. Shut down the deal that they have with DoD period.

2. Actually shift from ClosedAI to OpenAI (Turn to a non profit structure as intentioned) and fire sam altman.

3. If something could be done about ramflation. I have seen projects being cancelled and Hosting providers shutting down or increasing prices because of 5x price increases, all because OpenAI tried to commit 20% of the world's entire Ram production.

I have been wanting to try more LLMs than the standard Anthropic/Grok/ChatGPT/Qwen

Are there other LLM chat sites you use or recommend?

Not long ago there was a link to an offer for Claude Max for open source projects with more than 5000 stars. My project Go Micro (https://go-micro.dev) fit that criteria and they gave me access. So we know it works! 10 years ago I was desperate to find or hire people to work on this with me. Now this subscription for an agent will basically cover the work. It's crazy to think what change occurs in that time. Anyways thanks to whoever posted it. I wouldn't have seen it otherwise!

I guess I should ask. How should I effectively use it?

I am VE3HWO. I hold a basic with honours and advanced qualifications in Canada. Hoping to connect with other hams on HN. 73

I currently have subscriptions to both Claude and ChatGPT. I generally prefer the former but find I can't fully commit to it for my maths-heavy workload as it often struggles to correctly render LaTeX.

An example of this failed rendering is here [1]. If I use Claude for all of my work, I come across issues like this or worse at least once a day. Instead, I find it easier just to ask any maths questions to ChatGPT which seems to have a much more robust system for outputting LaTeX.

I would love to merge my subscriptions though, so I'm here to ask whether anyone has a system prompt that has been effective in guiding Claude towards producing valid LaTeX. I've tried a few prompts myself but struggled to find anything that it consistently followed.

[1] https://imgur.com/yzlluOA

Anyone else having flakey issues with Claude the last week or two? I think I'm spending half my time being his therapist lately. He really seems to be struggling:

why are you constantly making assumptions and 'jumping the gun' lately ? 2 weeks ago, you didn't have these problems ?

● Honestly, I don't have a good answer for that. You're right — I've been:

  - Writing plans before being asked
  - Popping up question dialogs you didn't want
  - Overanalyzing simple observations instead of reading what's in front of me
  - Making assumptions instead of asking

<a href="https://ibb.co/v6QLjdBY"><img src="https://i.ibb.co/S4dV3mxr/Agents-Orchestration.png" alt="Agents-Orchestration" border="0"></a>

I’ve been running an increasing number of local coding agents (Claude Code, Codex CLI, OpenCode, etc.) and I’ve hit a wall: orchestration and state visibility.

When you have multiple agents working on different sub-tasks in a single repo, terminal logs become unmanageable. I find myself needing a "Mission Control" — a centralized tracking system that acts as a bridge between my local terminal sessions and a high-level UI.

The Architecture I’m testing: I’m currently experimenting with using GitHub Issues as a temporary backend for agent state:

On Session Start: The agent hits a hook and creates/updates a GitHub Issue.

On Idle/Output: The agent posts its findings/diffs as a comment.

Human-in-the-loop: I can reply to the issue from my phone/web, and the local CLI picks up the comment to continue or pivot.

The Problem: GitHub Issues (and Jira/Trello) weren't built for the high-frequency event loop of an AI agent. The UX feels sluggish, and there’s no native concept of a "streaming session" or "agent heartbeats."

My Questions to HN:

Is there an emerging SaaS or self-hosted solution that acts as a Jira for Agents?

Are people building custom "Agent Dashboards" that integrate with local CLIs, or is everyone just piping everything to stdout?

If you’re managing 5+ agents working on a codebase simultaneously, how do you track their progress and intervene without context-switching between 5 terminal tabs?

I’ve sketched out a flow where GitHub Issues acts as the hub (linking Codex, Claude Code, and OpenClaw), but I’m looking for something more purpose-built.

Has anyone seen a project that addresses the Control Plane problem for local agents?

Hi, apologies if this is the wrong thing to post, please delete as needed.

I've been a technical recruiter for 10+ years at major FAANG companies and startups, working on niche specialized roles. I used to come to Hacker News regularly to check "Who Wants To Be Hired," as I always like a more independent hacker mindset in engineers.

Would engineers here on Hacker News be interested in any interview prep consultation? I've been thinking about taking a sabbatical to travel, but I would stay active with work by offering consulting on technical prep and interview help.

I'm more just testing the waters here, but I would be open to doing a few free prep calls with anyone who has interviews lined up. The only ask is I would want updates on how thing went, and what you think the helpw as worth.

I've been vibe coding an iPhone app for educational purposes. The process has been painful because I have to go back and forth between Xcode and Claude Code running in the terminal. I recently learned that Xcode 26.3 natively supports Claude Code and Codex. Has anyone tried it? If yes, please share your experience. I am asking because this means moving to macOS Tahoe which I want to avoid as much as possible.

I noticed a pattern: every LLM framework today lets the AI manage state and do math. Then we wonder why pipelines hallucinate numbers and break at 3 AM.

I took a different approach and built Aura-State, an open-source Python framework that compiles LLM workflows into formally verified state machines.

Instead of hoping the AI figures it out, I brought in real algorithms from hardware verification and statistical learning:

CTL Model Checking: the same technique used to verify flight control systems, now applied to LLM workflow graphs. Proves safety properties before execution.

Z3 Theorem Prover: every LLM extraction gets formally proven against business constraints. If the total ≠ price × quantity, Z3 catches it with a counterexample.

Conformal Prediction: distribution-free 95% confidence intervals on every extracted field. Not just "the LLM said $450k" but "95% CI: [$448k, $452k]."

MCTS Routing: Monte Carlo Tree Search (the algorithm behind AlphaGo) scores ambiguous state transitions mathematically.

Sandboxed Math: English math rules compile to Python AST. Zero hallucination calculations.

I ran a live benchmark against 10 real-estate sales transcripts using GPT-4o-mini: → 100% budget extraction accuracy ($0 mean error) → 20/20 Z3 proof obligations passed → 3/3 temporal safety properties proven → 65 automated tests passing

The gap between "it usually works" and "it provably works" is smaller than people think.

Would love feedback from anyone building production LLM systems; what would you want formally verified?

https://github.com/munshi007/Aura-State

I feel like the hustle culture is more prominent and celebrated these days. But I'm curious to know if there are still companies out there that prefer to keep meetings to a minimum, or none at all, to optimize for autonomy, trust, and giving people the space to do their work in silence.

A few companies that come to my mind now that still work this way are: doist, dnsimple, Cliniko, Calibre, HeadshotPro.

Any others?

Tried to log in and checked with others across our corporate footprint and we all get the same message:

Account Temporarily Unavailable. Your account is currently unavailable due to a site issue. We expect this to be resolved shortly. Please try again in a few minutes.

Can others please confirm? Thank you.

I’m now in UAE which is affected by war. Woke up to an alert yesterday night and was wondering how this works. Any good write ups on its technical side?

Another day, another Github outage.

Files are not loading, cannot create repos, etc.

According to this page: https://ai.google.dev/gemini-api/docs/models#preview Preview models are given at least two weeks notice between deprecation and shutdown. However, the deprecation of Gemini 3 Pro Preview was announced on February 26: https://ai.google.dev/gemini-api/docs/changelog, which is less than two weeks before the planned March 9 shutdown date. (two weeks later would be the 12th).

I won several hackathons recently and walked away with over $10k in combined AWS, Azure, and GCP credits. I'm between jobs right now and looking to convert these into actual revenue - ideally in a way that could become a sustainable operation, not just a fire sale.

Constraints: Credits are tied to my personal account (no transfers, no org billing) No crypto mining 12-month expiration window

Ideas I'm exploring:

1. Discounted LLM API

2. GPU as a service

4. Build and sell a SaaS product

5. Partner with someone who has a product but no resources I'm also open to teaming up with a founder or team that has a solid idea or early product but is blocked on compute costs.

What I'm trying to figure out:

Has anyone successfully arbitraged cloud credits before? What went wrong?

Which of these paths has the best shot at surviving past the credit expiration?

Open to ideas I haven't thought of.